# flake8: noqa
# Lint as: python3

from typing import Dict, List, Optional, Type

from .. import config
from ..utils import logging
from .formatting import (
    ArrowFormatter,
    CustomFormatter,
    Formatter,
    PandasFormatter,
    PythonFormatter,
    TensorFormatter,
    format_table,
    query_table,
)
from .np_formatter import NumpyFormatter


lowerCamelCase__  =					logging.get_logger(__name__)

lowerCamelCase__  =					{}
lowerCamelCase__  =					{}
lowerCamelCase__  =					{}


def 				lowerCAmelCase__       (			a__    ,     a__    ,     a__ = None    ,     )      ->List[str]:




  '''simple docstring'''

  _UpperCamelCase           =    aliases if aliases is not None else []
  if format_type in _FORMAT_TYPES:
    logger.warning(
        f'Overwriting format type \'{format_type}\' ({_FORMAT_TYPES[format_type].__name__} -> {formatter_cls.__name__})' )
  _UpperCamelCase           =    formatter_cls
  for alias in set(aliases + [format_type] ):
    if alias in _FORMAT_TYPES_ALIASES:
      logger.warning(
          f'Overwriting format type alias \'{alias}\' ({_FORMAT_TYPES_ALIASES[alias]} -> {format_type})' )
    _UpperCamelCase           =    format_type


def 				lowerCAmelCase__       (			a__    ,     a__    ,     a__ = None )      ->List[Any]:




  '''simple docstring'''

  _UpperCamelCase           =    aliases if aliases is not None else []
  for alias in set(aliases + [format_type] ):
    _UpperCamelCase           =    unavailable_error


# Here we define all the available formatting functions that can be used by `Dataset.set_format`
_register_formatter(PythonFormatter, None, aliases=['''python'''])
_register_formatter(ArrowFormatter, '''arrow''', aliases=['''pa''', '''pyarrow'''])
_register_formatter(NumpyFormatter, '''numpy''', aliases=['''np'''])
_register_formatter(PandasFormatter, '''pandas''', aliases=['''pd'''])
_register_formatter(CustomFormatter, '''custom''')

if config.TORCH_AVAILABLE:
   from .torch_formatter import TorchFormatter

   _register_formatter(TorchFormatter, '''torch''', aliases=['''pt''', '''pytorch'''])
else:
   lowerCamelCase__  =					ValueError('''PyTorch needs to be installed to be able to return PyTorch tensors.''')
   _register_unavailable_formatter(_torch_error, '''torch''', aliases=['''pt''', '''pytorch'''])

if config.TF_AVAILABLE:
   from .tf_formatter import TFFormatter

   _register_formatter(TFFormatter, '''tensorflow''', aliases=['''tf'''])
else:
   lowerCamelCase__  =					ValueError('''Tensorflow needs to be installed to be able to return Tensorflow tensors.''')
   _register_unavailable_formatter(_tf_error, '''tensorflow''', aliases=['''tf'''])

if config.JAX_AVAILABLE:
   from .jax_formatter import JaxFormatter

   _register_formatter(JaxFormatter, '''jax''', aliases=[])
else:
   lowerCamelCase__  =					ValueError('''JAX needs to be installed to be able to return JAX arrays.''')
   _register_unavailable_formatter(_jax_error, '''jax''', aliases=[])


def 				lowerCAmelCase__       (			a__ )      ->Optional[str]:




  '''simple docstring'''

  if format_type in _FORMAT_TYPES_ALIASES:
    return _FORMAT_TYPES_ALIASES[format_type]
  else:
    return format_type







def 				lowerCAmelCase__       (			a__    ,     **a__ )      ->Formatter:




  '''simple docstring'''

  _UpperCamelCase           =    get_format_type_from_alias(a__ )
  if format_type in _FORMAT_TYPES:
    return _FORMAT_TYPES[format_type](**a__ )
  if format_type in _FORMAT_TYPES_ALIASES_UNAVAILABLE:
    raise _FORMAT_TYPES_ALIASES_UNAVAILABLE[format_type]
  else:
    raise ValueError(
        f'Return type should be None or selected in {list(type for type in _FORMAT_TYPES.keys() if type != None )}, but got \'{format_type}\'' )





from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
   if not (is_transformers_available() and is_torch_available()):
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   from ...utils.dummy_torch_and_transformers_objects import KandinskyPipeline, KandinskyPriorPipeline
else:
   from .pipeline_kandinsky import KandinskyPipeline
   from .pipeline_kandinsky_imgaimg import KandinskyImgaImgPipeline
   from .pipeline_kandinsky_inpaint import KandinskyInpaintPipeline
   from .pipeline_kandinsky_prior import KandinskyPriorPipeline, KandinskyPriorPipelineOutput
   from .text_encoder import MultilingualCLIP




